AI vendor dependency is becoming a resilience risk

AI integration into enterprise operations has become ubiquitous, enabling tasks ranging from data analysis to decision-making. However, the conversation often overlooks the significant risk of AI vendor dependency becoming a resilience risk. While the focus is on AI's capabilities, productivity, and accuracy, little attention is given to the potential impact when access to AI capabilities is suddenly disrupted.

The Anthropic controversy surrounding its Fable and Mythos AI models exemplifies this issue, primarily centered on compliance timelines and export control mechanics. Yet, the real question should be why organizations are so reliant on external decisions that can suddenly remove critical business capabilities. This dependency exposes a critical governance gap around AI access and highlights the need to shift focus from AI security to its resilience.

Security and resilience are distinct concepts; security prevents system compromise, while resilience enables continued operations despite system unavailability. With AI's growing influence, organizations must now plan for disrupted access to critical tools and functions due to geopolitical decisions, regulations, or technology provider changes.

Traditional software dependency is typically between a few vendors, but AI often involves an interconnected ecosystem of providers, introducing multiple points of failure. The four key risk factors include data sovereignty, model sovereignty, infrastructure dependency, and AI supply chain risks. These factors increasingly depend on geopolitics rather than technology.

Governance frameworks must evolve to account for this issue, recognizing that vendor contracts alone cannot guarantee uninterrupted access. Organizations should develop contingency plans to ensure smooth operations during disruptions and treat AI as any other critical third-party vendor. Before new disruptions, boards should scrutinize AI capability claims, require measurable outcomes, and rely on human expertise to validate findings and prioritize fixes.

The key takeaway is the underestimated dependence on uncontrollable technology, with renewed legislative focus on AI "kill switches" making it a top priority for business leaders.